Quarterly Census of Employment and Wages

County Employment and Wages News Release

For release 10:00 a.m. (EST), Tuesday, December 5, 2017 USDL-17-1613
Technical Information: (202) 691-6567 * QCEWInfo@bls.gov * www.bls.gov/cew
Media Contact: (202) 691-5902 * PressOffice@bls.gov
COUNTY EMPLOYMENT AND WAGES
Second Quarter 2017
From June 2016 to June 2017, employment increased in 318 of the 346 largest U.S. counties, the U.S.
Bureau of Labor Statistics reported today. Midland, Texas, had the largest percentage increase with a
gain of 7.3 percent over the year, above the national job growth rate of 1.7 percent. Within Midland, the
largest employment increase occurred in natural resources and mining, which gained 3,497 jobs over the
year (19.6 percent). Lucas, Ohio, had the largest over-the-year percentage decrease in employment
among the largest counties in the U.S., with a loss of 1.9 percent. Within Lucas, construction had the
largest decrease in employment, with a loss of 1,534 jobs (-14.2 percent).
The U.S. average weekly wage increased 3.2 percent over the year, growing to $1,020 in the second
quarter of 2017. New Hanover, N.C., had the largest over-the-year percentage increase in average
weekly wages with a gain of 11.9 percent. Within New Hanover, an average weekly wage gain of $589
(62.7 percent) in professional and business services made the largest contribution to the county’s
increase in average weekly wages. McLean, Ill., had the largest over-the-year percentage decrease in
average weekly wages with a loss of 20.4 percent. Within McLean, financial activities had the largest
impact on the county’s average weekly wage change with a decrease of $953 (-38.9 percent) over the
year.
County employment and wage data are from the Quarterly Census of Employment and Wages (QCEW)
program, which provides the only detailed quarterly and annual universe count of establishments,
employment, and wages at the county, metropolitan statistical area, state, and national levels by detailed
industry. These data are published within 6 months following the end of each quarter.
Large County Employment
In June 2017, national employment was 145.2 million (as measured by the QCEW program). Over the
year, employment increased 1.7 percent, or 2.4 million. In June 2017, the 346 U.S. counties with 75,000
or more jobs accounted for 72.7 percent of total U.S. employment and 77.7 percent of total wages. These
346 counties had a net job growth of 1.8 million over the year, accounting for 76.8 percent of the overall
U.S. employment increase. The 5 counties with the largest increases in employment levels had a
combined over-the-year employment gain of 258,900 jobs, which was 10.8 percent of the overall job
increase for the U.S. (See table A.)
Employment declined in 23 of the largest counties from June 2016 to June 2017. Lucas, Ohio, had the
largest over-the-year percentage decrease in employment (-1.9 percent), followed by Caddo, La.;
Kanawha, W.Va.; Shawnee, Kan.; and Anchorage, Alaska. (See table 1.)
Table A. Large counties ranked by June 2017 employment, June 2016-17 employment increase, and
June 2016-17 percent increase in employment
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Employment in large counties
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June 2017 employment | Increase in employment, | Percent increase in employment,
(thousands) | June 2016-17 | June 2016-17
| (thousands) |
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| |
United States 145,186.4| United States 2,407.0| United States 1.7
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| |
Los Angeles, Calif. 4,373.6| Los Angeles, Calif. 71.9| Midland, Texas 7.3
Cook, Ill. 2,598.4| Maricopa, Ariz. 61.2| Weld, Colo. 5.3
New York, N.Y. 2,469.1| King, Wash. 44.2| Utah, Utah 5.2
Harris, Texas 2,284.5| New York, N.Y. 41.1| York, S.C. 4.8
Maricopa, Ariz. 1,891.7| Dallas, Texas 40.5| Elkhart, Ind. 4.7
Dallas, Texas 1,686.9| Orange, Calif. 33.2| Davis, Utah 4.5
Orange, Calif. 1,598.1| San Diego, Calif. 28.9| Clark, Wash. 4.4
San Diego, Calif. 1,440.9| Fulton, Ga. 27.9| Deschutes, Ore. 4.3
King, Wash. 1,369.7| Clark, Nev. 26.9| Boone, Ky. 4.2
Miami-Dade, Fla. 1,111.0| Orange, Fla. 26.5| Williamson, Tenn. 4.1
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Large County Average Weekly Wages
Average weekly wages for the nation increased to $1,020, a 3.2 percent increase, during the year ending
in the second quarter of 2017. Among the 346 largest counties, 325 had over-the-year increases in
average weekly wages. New Hanover, N.C., had the largest percentage wage increase among the largest
U.S. counties (11.9 percent). (See table B.)
Of the 346 largest counties, 19 experienced an over-the-year decrease in average weekly wages.
McLean, Ill., had the largest percentage decrease in average weekly wages (-20.4 percent), followed by
Union, N.J.; Warren, Ohio; Somerset, N.J.; Fairfield, Conn.; and Washington, Ore. (See table 1.)
Table B. Large counties ranked by second quarter 2017 average weekly wages, second quarter 2016-17
increase in average weekly wages, and second quarter 2016-17 percent increase in average weekly wages
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Average weekly wage in large counties
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Average weekly wage, | Increase in average weekly | Percent increase in average
second quarter 2017 | wage, second quarter 2016-17 | weekly wage, second
| | quarter 2016-17
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| |
United States $1,020| United States $32| United States 3.2
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| |
Santa Clara, Calif. $2,392| San Mateo, Calif. $214| New Hanover, N.C. 11.9
San Mateo, Calif. 2,093| Santa Clara, Calif. 141| San Mateo, Calif. 11.4
San Francisco, Calif. 1,941| Midland, Texas 135| Midland, Texas 11.4
New York, N.Y. 1,907| San Francisco, Calif. 132| Kitsap, Wash. 11.0
Washington, D.C. 1,675| Morris, N.J. 102| Clackamas, Ore. 10.0
Suffolk, Mass. 1,651| Kitsap, Wash. 97| Bell, Texas 9.6
Arlington, Va. 1,609| New Hanover, N.C. 94| St. Louis, Minn. 9.5
Fairfax, Va. 1,542| Clackamas, Ore. 93| Newport News City, Va. 7.4
Morris, N.J. 1,525| King, Wash. 83| San Francisco, Calif. 7.3
Middlesex, Mass. 1,522| Bell, Texas 77| Washington, Ark. 7.2
| | Morris, N.J. 7.2
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Ten Largest U.S. Counties
All of the largest counties had over-the-year percentage increases in employment in June 2017. King,
Wash., and Maricopa, Ariz., had the largest gain (3.3 percent). Within King, trade, transportation, and
utilities had the largest over-the-year employment level increase, with a gain of 16,004 jobs, or 6.4
percent. Within Maricopa, education and health services had the largest over-the-year employment level
increase, with a gain of 11,768 jobs, or 4.2 percent. Cook, Ill., had the lowest percentage increase in
employment among the 10 largest counties (0.3 percent). Within Cook, leisure and hospitality had the
largest over-the-year employment level increase, with a gain of 7,020 jobs, or 2.4 percent. (See table 2.)
Average weekly wages increased over the year in 9 of the 10 largest U.S. counties. King, Wash.,
experienced the largest percentage gain in average weekly wages (6.0 percent). Within King, trade,
transportation, and utilities had the largest impact on the county’s average weekly wage growth. Within
trade, transportation, and utilities, average weekly wages increased by $183, or 12.8 percent, over the
year. Harris, Texas, had the only percent loss in average weekly wages among the 10 largest counties
(-0.4 percent). Within Harris, natural resources and mining had the largest impact on the county’s average
weekly wage growth with a decrease of $290 (-9.0 percent) over the year.
For More Information
The tables included in this release contain data for the nation and for the 346 U.S. counties with annual
average employment levels of 75,000 or more in 2016. June 2017 employment and 2017 second quarter
average weekly wages for all states are provided in table 3 of this release.
The data are derived from reports submitted by employers who are subject to unemployment insurance
(UI) laws. The 9.9 million employer reports cover 145.2 million full- and part-time workers. Data for the
second quarter of 2017 will be available later at www.bls.gov/cew. Additional information about the
quarterly employment and wages data is available in the Technical Note. More information about
QCEW data may be obtained by calling (202) 691-6567.
The most current news release on quarterly measures of gross job flows is available from QCEW
Business Employment Dynamics at www.bls.gov/news.release/pdf/cewbd.pdf.
Several BLS regional offices issue QCEW news releases targeted to local data users. Links to these
releases are available at www.bls.gov/cew/cewregional.htm.
_____________
The County Employment and Wages release for third quarter 2017 is scheduled to be released on
Thursday, March 8, 2018.

Technical Note
These data are the product of a federal-state cooperative program, the Quarterly Census of
Employment and Wages (QCEW) program, also known as the ES-202 program. The data are
derived from summaries of employment and total pay of workers covered by state and federal
unemployment insurance (UI) legislation and provided by State Workforce Agencies (SWAs). The
summaries are a result of the administration of state unemployment insurance programs that
require most employers to pay quarterly taxes based on the employment and wages of workers
covered by UI. QCEW data in this release are based on the 2017 North American Industry
Classification System (NAICS). Data for 2017 are preliminary and subject to revision.
For purposes of this release, large counties are defined as having employment levels of 75,000 or
greater. In addition, data for San Juan, Puerto Rico, are provided, but not used in calculating U.S.
averages, rankings, or in the analysis in the text. Each year, these large counties are selected on the
basis of the preliminary annual average of employment for the previous year. The 347 counties
presented in this release were derived using 2016 preliminary annual averages of employment. For
2017 data, three counties have been added to the publication tables: Sussex, Del.; Maui + Kalawao,
Hawaii; and Deschutes, Ore. These counties will be included in all 2017 quarterly releases. One
county, Gregg, Texas, which was published in the 2016 releases, will be excluded from this and
future 2017 releases because its 2016 annual average employment level was less than 75,000. The
counties in table 2 are selected and sorted each year based on the annual average employment from
the preceding year
The preliminary QCEW data presented in this release may differ from data released by the
individual states. These potential differences result from the states' continuing receipt of UI data
over time and ongoing review and editing. The individual states determine their data release
timetables.
Differences between QCEW, BED, and CES employment measures
The Bureau publishes three different establishment-based employment measures for any given
quarter. Each of these measures--QCEW, Business Employment Dynamics (BED), and Current
Employment Statistics (CES)--makes use of the quarterly UI employment reports in producing
data; however, each measure has a somewhat different universe coverage, estimation procedure,
and publication product.
Differences in coverage and estimation methods can result in somewhat different measures of
employment change over time. It is important to understand program differences and the intended
uses of the program products. (See table.) Additional information on each program can be obtained
from the program Web sites shown in the table.
Summary of Major Differences between QCEW, BED, and CES Employment Measures
----------------------------------------------------------------------------------
| QCEW | BED | CES
-----------|---------------------|----------------------|------------------------
Source |--Count of UI admini-|--Count of longitudi- |--Sample survey:
| strative records | nally-linked UI ad- | 634,000 establish-
| submitted by 9.9 | ministrative records| ments
| million establish- | submitted by 7.9 |
| ments in first | million private-sec-|
| quarter of 2017 | tor employers |
-----------|---------------------|----------------------|------------------------
Coverage |--UI and UCFE cover- |--UI coverage, exclud-|Nonfarm wage and sal-
| age, including all | ing government, pri-| ary jobs:
| employers subject | vate households, and|--UI coverage, exclud-
| to state and fed- | establishments with | ing agriculture, pri-
| eral UI laws | zero employment | vate households, and
| | | self-employed workers
| | |--Other employment, in-
| | | cluding railroads,
| | | religious organiza-
| | | tions, and other non-
| | | UI-covered jobs
-----------|---------------------|----------------------|------------------------
Publication|--Quarterly |--Quarterly |--Monthly
frequency | -Within 6 months | -7 months after the | -Usually the 3rd Friday
| after the end of | end of each quarter| after the end of the
| each quarter | | week including
| | | the 12th of the month
-----------|---------------------|----------------------|------------------------
Use of UI |--Directly summarizes|--Links each new UI |--Uses UI file as a sam-
file | and publishes each | quarter to longitu- | pling frame and to an-
| new quarter of UI | dinal database and | nually realign sample-
| data | directly summarizes | based estimates to pop-
| | gross job gains and | ulation counts (bench-
| | losses | marking)
-----------|---------------------|----------------------|------------------------
Principal |--Provides a quarter-|--Provides quarterly |--Provides current month-
products | ly and annual uni- | employer dynamics | ly estimates of employ-
| verse count of es- | data on establish- | ment, hours, and earn-
| tablishments, em- | ment openings, clos-| ings at the MSA, state,
| ployment, and wages| ings, expansions, | and national level by
| at the county, MSA,| and contractions at | industry
| state, and national| the national level |
| levels by detailed | by NAICS supersec- |
| industry | tors and by size of |
| | firm, and at the |
| | state private-sector|
| | total level |
| |--Future expansions |
| | will include data |
| | with greater indus- |
| | try detail and data |
| | at the county and |
| | MSA level |
-----------|---------------------|----------------------|------------------------
Principal |--Major uses include:|--Major uses include: |--Major uses include:
uses | -Detailed locality | -Business cycle | -Principal federal
| data | analysis | economic indicator
| -Periodic universe | -Analysis of employ-| -Official time series
| counts for bench- | er dynamics under- | for employment change
| marking sample | lying economic ex- | measures
| survey estimates | pansions and con- | -Input into other ma-
| -Sample frame for | tractions | jor economic indi-
| BLS establishment | -Analysis of employ-| cators
| surveys | ment expansion and |
| | contraction by size|
| | of firm |
| | |
-----------|---------------------|----------------------|------------------------
Program |--www.bls.gov/cew/ |--www.bls.gov/bdm/ |--www.bls.gov/sae/
Web sites | | |
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Coverage
Employment and wage data for workers covered by state UI laws are compiled from quarterly
contribution reports submitted to the SWAs by employers. For federal civilian workers covered by
the Unemployment Compensation for Federal Employees (UCFE) program, employment and
wage data are compiled from quarterly reports submitted by four major federal payroll processing
centers on behalf of all federal agencies, with the exception of a few agencies which still report
directly to the individual SWA. In addition to the quarterly contribution reports, employers who
operate multiple establishments within a state complete a questionnaire, called the "Multiple
Worksite Report," which provides detailed information on the location and industry of each of their
establishments. QCEW employment and wage data are derived from microdata summaries of 9.7
million employer reports of employment and wages submitted by states to the BLS in 2016. These
reports are based on place of employment rather than place of residence.
UI and UCFE coverage is broad and has been basically comparable from state to state since 1978,
when the 1976 amendments to the Federal Unemployment Tax Act became effective, expanding
coverage to include most state and local government employees. In 2016, UI and UCFE programs
covered workers in 141.9 million jobs. The estimated 136.6 million workers in these jobs (after
adjustment for multiple jobholders) represented 96.4 percent of civilian wage and salary
employment. Covered workers received $7.607 trillion in pay, representing 94.1 percent of the
wage and salary component of personal income and 40.9 percent of the gross domestic product.
Major exclusions from UI coverage include self-employed workers, most agricultural workers on
small farms, all members of the Armed Forces, elected officials in most states, most employees of
railroads, some domestic workers, most student workers at schools, and employees of certain small
nonprofit organizations.
State and federal UI laws change periodically. These changes may have an impact on the
employment and wages reported by employers covered under the UI program. Coverage changes
may affect the over-the-year comparisons presented in this news release.
Concepts and methodology
Monthly employment is based on the number of workers who worked during or received pay for
the pay period including the 12th of the month. With few exceptions, all employees of covered
firms are reported, including production and sales workers, corporation officials, executives,
supervisory personnel, and clerical workers. Workers on paid vacations and part-time workers also
are included.
Average weekly wage values are calculated by dividing quarterly total wages by the average of the
three monthly employment levels (all employees, as described above) and dividing the result by
13, for the 13 weeks in the quarter. These calculations are made using unrounded employment and
wage values. The average wage values that can be calculated using rounded data from the BLS
database may differ from the averages reported. Included in the quarterly wage data are non-wage
cash payments such as bonuses, the cash value of meals and lodging when supplied, tips and other
gratuities, and, in some states, employer contributions to certain deferred compensation plans such
as 401(k) plans and stock options. Over-the-year comparisons of average weekly wages may
reflect fluctuations in average monthly employment and/or total quarterly wages between the
current quarter and prior year levels.
Average weekly wages are affected by the ratio of full-time to part-time workers as well as the
number of individuals in high-paying and low-paying occupations and the incidence of pay periods
within a quarter. For instance, the average weekly wage of the workforce could increase
significantly when there is a large decline in the number of employees that had been receiving
below-average wages. Wages may include payments to workers not present in the employment
counts because they did not work during the pay period including the 12th of the month. When
comparing average weekly wage levels between industries, states, or quarters, these factors should
be taken into consideration.
Wages measured by QCEW may be subject to periodic and sometimes large fluctuations. This
variability may be due to calendar effects resulting from some quarters having more pay dates than
others. The effect is most visible in counties with a dominant employer. In particular, this effect
has been observed in counties where government employers represent a large fraction of overall
employment. Similar calendar effects can result from private sector pay practices. However, these
effects are typically less pronounced for two reasons: employment is less concentrated in a single
private employer, and private employers use a variety of pay period types (weekly, biweekly,
semimonthly, monthly).
For example, the effect on over-the-year pay comparisons can be pronounced in federal
government due to the uniform nature of federal payroll processing. Most federal employees are
paid on a biweekly pay schedule. As a result, in some quarters federal wages include six pay dates,
while in other quarters there are seven pay dates. Over-the-year comparisons of average weekly
wages may also reflect this calendar effect. Growth in average weekly wages may be attributed, in
part, to a comparison of quarterly wages for the current year, which include seven pay dates, with
year-ago wages that reflect only six pay dates. An opposite effect will occur when wages in the
current quarter reflecting six pay dates are compared with year-ago wages for a quarter including
seven pay dates.
In order to ensure the highest possible quality of data, states verify with employers and update, if
necessary, the industry, location, and ownership classification of all establishments on a 3-year
cycle. Changes in establishment classification codes resulting from this process are introduced with
the data reported for the first quarter of the year. Changes resulting from improved employer
reporting also are introduced in the first quarter.
QCEW data are not designed as a time series. QCEW data are simply the sums of individual
establishment records and reflect the number of establishments that exist in a county or industry at
a point in time. Establishments can move in or out of a county or industry for a number of reasons-
-some reflecting economic events, others reflecting administrative changes. For example,
economic change would come from a firm relocating into the county; administrative change would
come from a company correcting its county designation.
The over-the-year changes of employment and wages presented in this release have been adjusted
to account for most of the administrative corrections made to the underlying establishment reports.
This is done by modifying the prior-year levels used to calculate the over-the-year changes.
Percent changes are calculated using an adjusted version of the final 2016 quarterly data as the
base data. The adjusted prior-year levels used to calculate the over-the-year percent change in
employment and wages are not published. These adjusted prior-year levels do not match the
unadjusted data maintained on the BLS Web site. Over-the-year change calculations based on data
from the Web site, or from data published in prior BLS news releases, may differ substantially
from the over-the-year changes presented in this news release.
The adjusted data used to calculate the over-the-year change measures presented in this release
account for most of the administrative changes--those occurring when employers update the
industry, location, and ownership information of their establishments. The most common
adjustments for administrative change are the result of updated information about the county
location of individual establishments. Included in these adjustments are administrative changes
involving the classification of establishments that were previously reported in the unknown or
statewide county or unknown industry categories. Adjusted data account for improvements in
reporting employment and wages for individual and multi-unit establishments. To accomplish this,
adjustments were implemented to account for: administrative changes caused by multi-unit
employers who start reporting for each individual establishment rather than as a single entity (first
quarter of 2008); selected large administrative changes in employment and wages (second quarter
of 2011); and state verified improvements in reporting of employment and wages (third quarter of
2014). These adjustments allow QCEW to include county employment and wage growth rates in
this news release that would otherwise not meet publication standards.
The adjusted data used to calculate the over-the-year change measures presented in any County
Employment and Wages news release are valid for comparisons between the starting and ending
points (a 12-month period) used in that particular release. Comparisons may not be valid for any
time period other than the one featured in a release even if the changes were calculated using
adjusted data.
County definitions are assigned according to Federal Information Processing Standards
Publications (FIPS PUBS) as issued by the National Institute of Standards and Technology, after
approval by the Secretary of Commerce pursuant to Section 5131 of the Information Technology
Management Reform Act of 1996 and the Computer Security Act of 1987, Public Law 104-106.
Areas shown as counties include those designated as independent cities in some jurisdictions and,
in Alaska, those designated as census areas where counties have not been created. County data also
are presented for the New England states for comparative purposes even though townships are the
more common designation used in New England (and New Jersey). The regions referred to in this
release are defined as census regions.
Additional statistics and other information
Employment and Wages Annual Averages Online features comprehensive information by detailed
industry on establishments, employment, and wages for the nation and all states. The 2016 edition
of this publication, which was published in September 2017, contains selected data produced by
Business Employment Dynamics (BED) on job gains and losses, as well as selected data from the
first quarter 2017 version of this news release. Tables and additional content from the 2016 edition
of Employment and Wages Annual Averages Online are now available at
www.bls.gov/cew/cewbultn16.htm. The 2017 edition of Employment and Wages Annual Averages
Online will be available in September 2018.
News releases on quarterly measures of gross job flows also are available from BED at
www.bls.gov/bdm, (202) 691-6467, or data.bls.gov/cgi-bin/forms/bdm.
Information in this release will be made available to sensory impaired individuals upon request.
Voice phone: (202) 691-5200; TDD message referral phone number: (800) 877-8339.